When Robots Mix Cocktails

From March 27-29, 2023, the AAAI 2023 Spring Symposia will feature the symposium „Socially Responsible AI for Well-being“ by Takashi Kido (Teikyo University, Japan) and Keiki Takadama (The University of Electro-Communications, Japan). The venue is usually Stanford University. For staffing reasons, this year the conference will be held at the Hyatt Regency in San Francisco. On March 28, Prof. Dr. Oliver Bendel and Lea Peier will present their paper „How Can Bar Robots Enhance the Well-being of Guests?“. From the abstract: „This paper addresses the question of how bar robots can contribute to the well-being of guests. It first develops the basics of service robots and social robots. It gives a brief overview of which gastronomy robots are on the market. It then presents examples of bar robots and describes two models used in Switzerland. A research project at the School of Business FHNW collected empirical data on them, which is used for this article. The authors then discuss how the robots could be improved to increase the well-being of customers and guests and better address their individual wishes and requirements. Artificial intelligence can play an important role in this. Finally, ethical and social problems in the use of bar robots are discussed and possible solutions are suggested to counter these.“ More Information via aaai.org/conference/spring-symposia/sss23/.

Fig.: When robots mix cocktails

AAAI Symposium on AI for Well-being

As part of the AAAI 2023 Spring Symposia in San Francisco, the symposium „Socially Responsible AI for Well-being“ is organized by Takashi Kido (Teikyo University, Japan) and Keiki Takadama (The University of Electro-Communications, Japan). The AAAI website states: „For our happiness, AI is not enough to be productive in exponential growth or economic/financial supremacies but should be socially responsible from the viewpoint of fairness, transparency, accountability, reliability, safety, privacy, and security. For example, AI diagnosis system should provide responsible results (e.g., a high-accuracy of diagnostics result with an understandable explanation) but the results should be socially accepted (e.g., data for AI (machine learning) should not be biased (i.e., the amount of data for learning should be equal among races and/or locations). Like this example, a decision of AI affects our well-being, which suggests the importance of discussing ‚What is socially responsible?‘ in several potential situations of well-being in the coming AI age.“ (Website AAAI) According to the organizers, the first perspective is „(Individually) Responsible AI“, which aims to clarify what kinds of mechanisms or issues should be taken into consideration to design Responsible AI for well-being. The second perspective is „Socially Responsible AI“, which aims to clarify what kinds of mechanisms or issues should be taken into consideration to implement social aspects in Responsible AI for well-being. More information via www.aaai.org/Symposia/Spring/sss23.php#ss09.

Fig.: Golden Gate Bridge